By Karl Staser, MD, PhD, John F. DiPersio, MD, PhD, William Eades, Angela Goldfain, and Nathan Trujillo, PhD
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the most effective treatment for patients with high risk and relapsed hematologic malignancies. When donor T cells recognize the host as foreign, they induce an immune response against the host and may cause life-threatening graft-versus-host disease (GvHD), a major complication of allo-HSCT. Monitoring T cell subsets pre- and post- transplantation in correlation with patient outcomes may identify the key cell types mediating engraftment, relapse, GvHD, and drug response. Because there are numerous T cell subset populations, many of which are rare, increasing the types that can be detected simultaneously can provide an advantage in unbiased tracking and quantification.
Using samples from patients enrolled in allo-HSCT clinical trials, researchers at Washington University have designed an optimized 21-color panel (Figure 1) to be used on the ZE5 Cell Analyzer for the purpose of examining changes in T cell populations pre- and post-transplantation, during treatment, and in correlation with patient outcomes.
Flow cytometry is a powerful tool for gathering multiparameter data quickly and efficiently. High-throughput analysis was especially important in this study of more than 150 patient samples. The ZE5 instrument running the 21-color panel analyzed the samples at 2-3 minutes per sample, which preserved the quality of time-sensitive samples and allowed for efficient acquisition of data.
With the recent catalog expansion of fluorochrome-antibody pairings the possibility for more sophisticated experimental design is expanding. The ZE5 Cell Analyzer from Bio-Rad Laboratories Inc. (previously the YETI Cell Analyzer from Propel Labs) provides expanded capacity compared to previous systems. The ZE5 Cell Analyzer allows simultaneous measurement of up to 30 parameters at rates of up to 100,000 cells-per-second. The instrument is equipped with a high-throughput loader and samples can be analyzed from tubes or multi-well plates with options for temperature control and agitation.
With the increase of instrumentation capabilities, multi-color experiments can be expanded to gather more information from each sample, thus reducing the quantity and volume of sample required. This is especially relevant in the context of leukopenia following stem cell transplant where the quantity of sample is low and the subset populations within the sample are inherently rare.
However, the increase in instrument capacity can also amplify the complexity of experimental design and therefore necessitate diligent planning. It is imperative to select the right fluorochrome-antibody combinations to optimize population resolution and minimize spectral spillover and plot spreading. Fluorophore brightness and antigen density must be considered, while bearing in mind the optical design and filter configuration of the instrument, which affect detection efficiency and dynamic range. Proper antibody titration and preparation of controls also contribute to the iterative integrity of multi-color experiment design. In this optimized panel, more than 26 well-defined subpopulations can be identified, simultaneously providing quantification of major and minor cell types.
Materials and Methods
To design a panel with this complexity, the Fluorophore Selector in EverestTM Software along with other fluorescence viewers were used to refine fluorescent marker selection. Antibodies colocalized to the same cell (e.g. CD3 and CD4) were given additional consideration when they were balanced for antigen density to dye brightness. All antibodies were titrated and tested on four normal human peripheral blood samples.
After initial photo multiplier tube (PMT) standardization, detector voltages were fine tuned to minimize spillover while keeping CVs to lowest values. This approach carefully maintained the experiment populations within usable dynamic range boundaries determined by 8-peak bead references for each parameter. The highest compensation value was just over 70%, with most being under 10%. Digital plot spreading was minimal after compensation. Fluorescence-minus-one (FMO) controls were included for most fluorophores during the experimental design. Later, some FMO controls were excluded if they were not required for gating.
During acquisition on the ZE5 instrument, the 96- well plate input was used exclusively with 4⁰C temperature control enabled because the cells were unfixed. The instrument was set to agitate for 5 seconds per sample to maintain cell suspension. With an approximate event rate of 10,000 cells per second and a cell concentration of 1x106 cells / 200 μL in each well, gate limits were set to collect 100- 200K white blood cells. Unused sample was returned to the well. Everest Software was used for set up and acquisition, at which point the data files were exported as .fcs to FlowJo v10.2 for compensation, analysis and presentation.
Normal human peripheral blood mononuclear cells (PBMCs) were plotted on a forward scatter versus side scatter pulse height density plot with a polygon region placed around the white blood cell (WBC) population to exclude red cell debris (Figure 2). Following doublet discrimination (Figure 3), the live singlet cells were isolated using the Zombie UV Viability Dye (Figure 4). Major T cell subsets, regulatory T cells, T helpers, and myeloid cells were gated from the live singlet cells for further analysis.
Live singlet cells were separated into T cell, myeloid cell, and B cell populations (Figures 5 and 17) using a plot of CD3 versus CD20. For basic T cell analysis, CD4+ T cells (Figures 6 and 8) were gated to isolate central memory T cells, naïve T cells, and effector memory T cells using a plot of CD45RA versus CD197 (Figures 7 and 11). For regulatory T cell (Treg) analysis, CD4+ T cells were plotted against CD25 versus CD127, with Tregs defined as CD25+ and CD127lo/-. Activated T regs were detected using CD38 versus Human Leukocyte Antigen D Related (HLADR) (Figure 10). Further T helper cell (Th) subset analysis was performed by gating CD45RA- memory CD4+ T cells on CCR10 versus CD185 (Figure 12) to discriminate T follicular helper (Tfh) cells distinctly from other Th subsets. These non-Tfh Th cells were then identified as T helper type 1 (Th1), T helper type 2 (Th2), T helper type 9 (Th9), T helper type 17 (Th17), T helper type 22 (Th22), and T helper GMCSF- secreting (ThG) cells using CD196 versus CD194 (Figure 13) and CD183 versus CCR10 (Figures 15 and 16).
For myeloid sub-population analysis, CD20- and CD3- cells (Figure 17) were gated on CD14 versus HLADR to isolate monocytes and dendritic cells (Figure 18). Using HLADR versus CD16, monocytes were separated into classical, non-classical and myeloid derived suppressor cells (MDSC) (Figure 19). Dendritic cells were separated into plasmacytoid dendritic cells (pDCs) and monocytic dendritic cells (mDCs) using CD123 versus CD11c (Figure 20). Natural killer (NK) cells were isolated from the CD14-/HLADRpopulation using CD16 versus CD56 (Figure 21). Finally, CD20+ cells were gated to identify activated B cells using CD38 versus HLADR (Figure 22).
Human peripheral blood samples were stained, and data were acquired on the ZE5 Cell Analyzer. The resulting data were analyzed using FlowJo v10.2 Data Analysis Software. Figures 2-22 show the gating strategy used to identify the T cell subset populations of interest for the study. This information will be used to quickly and comprehensively immunophenotype patient samples from clinical trials of novel drugs aimed at enhancing the therapeutic benefit of allo-HSCT while minimizing GVHD.
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